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Talent500 is hiring for one of its clients. Who are we: Core Insurance Platforms (CIP) is Zurichs global capability responsible for building, running, and evolving core insurance technology. We set a unified, scalable operating modelcovering governance, standards, architecture, service delivery, and reuseso our business units can deliver at speed and scale. CIP is the strategic steward of Zurichs Guidewire ecosystem, aligning platform roadmaps to business strategy while driving stability, modernization, reduced supplier dependency, and long term cost efficiency. India delivery center is one of our global delivery and capability hub. We bring together experts in AI, engineering, analysis, quality, and architecture to deliver product & process solutions, application run services, change and transformation initiatives, and centralized platform services across both on prem and Guidewire Cloud environments. Our teams operate from multiple global delivery centers, supporting Zurichs business units worldwide. Role: Associate Staff Digital Employee Experience AI Engineer Value Proposition: Join the Digital Employee Experience function and help redefine how employees experience technology every day. As a DEX Factory AI Engineer, you will ideate, design and implement AI-powered solutions that automate IT operations and improve the employee experience at enterprise scale. You will work with modern Generative AI, agentic workflows and cloud-based engineering practices to solve real operational challenges and influence the future direction of digital workplace services. Mission Statement: To reimagine IT operations and employee experience through AI by delivering intelligent, reliable and secure automation that improves productivity, reduces friction and enables continuous innovation across enterprise platforms. Key Responsibilities: Ideate, design, prototype and implement AI solutions that automate IT operations and enhance employee experience.Translate operational pain points, incidents, requests and repetitive engineering tasks into AI-enabled automation opportunities with measurable business value.Build and maintain AI, ML and Generative AI components such as LLM-based assistants, RAG pipelines, orchestration workflows and intelligent remediation capabilities.Integrate AI solutions with enterprise platforms and data sources, including IT service management, endpoint management and employee experience tooling.Apply responsible AI, privacy, security and governance principles throughout design, development and deployment.Use engineering best practices including version control, peer review, testing, CI/CD and operational observability.Contribute to MLOps and LLMOps practices, including model evaluation, prompt quality, performance monitoring, drift awareness, safety controls and cost management.Collaborate with platform leads, architects, security teams and business stakeholders to shape scalable and supportable solutions.Document solutions clearly and support knowledge sharing across the team.Drive continuous improvement through experimentation, analytics and iterative delivery. Skills and Experience: The ideal candidate combines hands-on AI engineering capability with a practical product mindset and a strong interest in improving IT operations and digital employee experience. The role requires curiosity, sound judgment and the ability to move from concept to production. 3-5 years of software engineering, automation engineering or AI engineering experience, with evidence of delivering production solutions.University degree in Computer Science, Data Science, Engineering or equivalent relevant experience.Strong hands-on experience with Python and common AI or ML libraries and frameworks.Practical experience building LLM-based applications, including retrieval-augmented generation, prompt design, tool calling or agent-style workflows.Working knowledge of cloud AI services such as Azure OpenAI, Azure AI Foundry, AWS Bedrock or similar platforms.Experience integrating with enterprise APIs, data sources and automation platforms; familiarity with vector databases is beneficial.Understanding of AI security, privacy, responsible AI practices and relevant regulatory expectations including EU AI Act principles.Working knowledge of Azure DevOps or equivalent tooling for source control and CI/CD.Strong analytical, documentation and problem-solving skills.Strong communication and collaboration skills with the ability to work independently when required.Proficiency in written and spoken English.German, Italian or Spanish would be an advantage but are not essential. Beneficial Experience: Experience with agentic AI frameworks or orchestration patterns.Knowledge of ServiceNow, Microsoft Intune, Nexthink or Microsoft 365 and Copilot ecosystems.Exposure to MLOps or LLMOps tools, evaluation frameworks or model lifecycle management practices.Data engineering or analytics skills such as SQL, data pipelines .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.